ReviewGrounder: grounding AI-assisted peer review in evidence

ReviewGrounder is an AI-assisted peer-review system designed to address growing reviewer workloads while keeping final judgment with human reviewers, area chairs, editors, and researchers. Rather than relying on a single model to assess an entire paper, it uses a Review Drafter followed by specialized agents that investigate related literature, technical reasoning, and experimental evidence, before an aggregator combines their findings with a conference rubric into a cited, evidence-based review. The system aims to make critiques more specific and verifiable by linking comments to relevant paper sections, prior work, and evaluation criteria. According to results reported for ACL 2026, ReviewGrounder exceeded GPT-4.1 by 41% and GPT-4o by 135% across eight review-quality dimensions. Developed through a collaboration involving several universities and Lambda, the project is presented as part of a broader movement toward compute-intensive AI research agents that support scientific writing, experimentation, and evaluation.

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